How to use
The easiest way to go from daily sales to financial statements
From data prep to the confirm steps for accurate analysis
1. Getting started
Upload → quick confirm → report. Most fields are pre-filled — usually just a few clicks.
Upload a file
Drop a spreadsheet or JSON and we detect structure and headers automatically.
Quick confirm
Review industry, country, currency, and only when needed commercial area or column roles.
AI analysis & report
Get anomalies, seasonality, and benchmarks — then download PDF.
2. Prepare your data for better analysis
Common principles
- Include a date (or month) column for trends, seasonality, and anomaly detection.
- One header row is most reliable (rows 2–3 can still be detected).
- Keep numeric columns as pure numbers — don’t mix unit text like “won” or “units”.
- Total/subtotal rows are fine — we detect and separate them automatically.
Your uploaded data is never used to train AI models
Missing columns are OK. We analyze what you have and quietly skip metrics that can’t be computed.
Recommended columns by industry group
F&B (cafe, restaurant, delivery…)
Date, revenue, category/menu, channel (dine-in/delivery), transactions · nice to have: seats, delivery fee, delivery time
Retail / distribution
Date, revenue, category, channel/store · nice to have: inventory, shrinkage, fresh-food sales (grocery)
E-commerce
Date, GMV/revenue, orders, channel/category · nice to have: returns, ad spend/ROAS, AOV
SaaS / subscription
Date (month), MRR, customers, churn · nice to have: NRR, CAC, burn/runway
B2B services (IT consulting, agency…)
Date, revenue, project/client, utilization · nice to have: pipeline, billable hours, rate
Healthcare / wellness
Date, revenue, patients/members, new vs returning · nice to have: visit type, cancellation rate
Hospitality (hotel…)
Date, revenue, rooms/occupancy, ADR · nice to have: RevPAR, channel (OTA vs direct)
Education
Date, revenue, students, course · nice to have: new enrollments, churn, completion rate
Real estate / finance
Date, revenue/fees/returns, deal count · nice to have: vacancy, AUM, yield
Manufacturing / logistics / other
Date, revenue or production volume, defect rate, OEE · logistics: shipments/lead time · wholesale: accounts/inventory turns
3. Analysis flow
Each confirm step exists to improve accuracy. Most of the time it’s prefill + confirm.
- 1
Industry
KPIs, benchmarks, and actions depend on industry. Pick the closest match.
- 2
Country · language · currency · fiscal year
Sets report language, currency display, holidays, and fiscal calendar. No FX conversion — source currency stays as-is.
- 3
Commercial area (F&B only)(conditional)
Office vs tourist catchments change how we interpret spikes. Confirm the estimate from weekday/season patterns.
- 4
Schema roles (uncertain columns only)(conditional)
We ask only when stock vs flow (or similar) is ambiguous. Clear columns are auto-confirmed.
- 5
Run analysis
The server computes numbers; AI interprets and builds the report.
4. Supported file formats
Only these formats are accepted. UI copy and the file picker use the same list.
Excel(.xlsx/.xls/.xlsm), CSV/TSV, JSON